BACKGROUND AND AIMS: Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in diagnostic algorithms requires substantial expertise and experience. In this stud...
Best practice & research. Clinical gastroenterology
Nov 10, 2020
Gastric cancer is a common cause of death worldwide and its early detection is crucial to improve its prognosis. Its incidence varies throughout countries, and screening has been found to be cost-effective at least in high-incidence regions. Identifi...
BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but remain underdiagnosed. This feasibility project tested the utility of an artificial intelligence-based chatbot deployed to patients scheduled for colo...
Breast cancer is the most common cancer in women. Early diagnosis improves outcome and survival, which is the cornerstone of breast cancer treatment. Thermography has been utilized as a complementary diagnostic technique in breast cancer detection. A...
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Oct 27, 2020
BACKGROUND AND AIMS: A deep convolutional neural network (CNN) was used to achieve fast and accurate artificial intelligence (AI)-assisted diagnosis of early gastric cancer (GC) and other gastric lesions based on endoscopic images.
Gastrointestinal endoscopy clinics of North America
Oct 26, 2020
Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neoplastic lesions, many new endoscopic imaging and sampling techniques have been developed. None of these...
The Korean journal of internal medicine
Oct 23, 2020
BACKGROUND/AIMS: We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal neoplasia (ACRN) in asymptomatic adults, based on which colorectal cancer screening could be customized.
Journal of the American College of Radiology : JACR
Oct 12, 2020
OBJECTIVE: To investigate the general population's view on the use of artificial intelligence (AI) for the diagnostic interpretation of screening mammograms.